Fluid Catalytic Cracking Catalyst for Reformulated Gasolines. Kinetic Modeling

Gianetto, A.; Farag, Hany; Blasetti, A.P.; Lasa, Hugo I. de

doi:10.1021/ie00036a021

Cited by 62 publications

(62 citation statements)

References 7 publications

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“…In reactors, from 5–21 mm in diameter, the gas phase is close to plug flow in shallow beds with an expanded bed height of 20 mm . The riser simulator is a microreator that suspends catalyst and recirculates gas at a high rate to maintain differential conditions in the bed but high overall conversion …”

Section: Uncertaintymentioning

confidence: 99%

“…[5] The riser simulator is a microreator that suspends catalyst and recirculates gas at a high rate to maintain differential conditions in the bed but high overall conversion. [58] The fluidization characteristics-bed expansion, bubble size, and flow characteristics-are superior with rounded particles, which are produced in spray dryers. However, the yield in small scale spray dryers is much less than 50 % so producing a precious metal catalyst becomes expensive.…”

Section: Uncertaintymentioning

confidence: 99%

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Experimental methods in chemical engineering: Reactors—fluidized beds

et al. 2019

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Industry relies on fluidized beds to synthesize chemicals (acrylonitrile, maleic anhydride, titanium dioxide, vinyl chloride), combust coal, dry powders, and treat waste. Fluidized bed folklore declares that they are hard to scale‐up and the gas phase is backmixed. Commercial failures that disregard standard design criteria around powder management, gas/solids injection, and mixing reinforce this belief. However, engineers select fluidized beds for processes that are impractical with conventional technologies to achieve economies of scale for highly exothermic, endothermic, or explosive reactions, for catalysts that deactivate in seconds (or minutes), and for chemistry that requires multiple dosing cycles. Failures are more frequent for these challenging applications. For this reason, researchers study reaction kinetics in fixed beds despite internal mass transfer limitations and axial and radial temperature and concentration gradients. Fluidized bed hydrodynamics vary with powder properties (particle diameter, size distribution, density, sphericity), operating conditions (gas density, viscosity, temperature, pressure), reactor geometry (diameter, height, mass, grid geometry). The minimum fluidization velocity (Umf) is a property that identifies the transition from the fixed bed regime to the fluidized bed regime and equals the gas velocity at which the upward drag force equals the weight of the powder. At the experimental scale, fluidized beds operate isothermally, solids are completely backmixed, and the gas phase is close to plug flow (Ug<-0.25em3Umf). Here, we describe the relationship between powder properties and fluidization quality, list experimental techniques, describe recent applications, and gas phase hydrodynamics and uncertainties.

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Section: Uncertaintymentioning

confidence: 99%

Section: Uncertaintymentioning

confidence: 99%

Experimental methods in chemical engineering: Reactors—fluidized beds

et al. 2019

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“…The variable SSA is the catalyst particle Specific Surface Area given in m 2 per catalyst weight and is used under the assumption that the wall area at each boundary cell represents the real pore area available for catalytic cracking reactions. Reaction rate kinetics are taken from the work of Gianetto et al [41], and are presented in Table 1. Reaction rate and kinetic constant k are given by the following expressions [41]: Evaporation source terms incorporated in respective equations and cracking reaction kinetics (preexponential factor, activation energy and specific surface area) used for 2-lump scheme taken from [41].…”

Section: Surface Reactions Modellingmentioning

confidence: 99%

Numerical investigation of heavy fuel droplet-particle collisions in the injection zone of a Fluid Catalytic Cracking reactor, Part I: Numerical model and 2D simulations

Malgarinos

Νikolopoulos

Gavaises

2017

Fuel Processing Technology

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractThe present paper investigates the collisions between heavy gasoil droplets and solid catalytic particles taking place at conditions realized in Fluid Catalytic Cracking reactors (FCC). The computational model utilizes the Navier-Stokes equations along with the energy conservation and transport of species equations. The VOF methodology is used in order to track the liquid-gas interface, while a dynamic local grid refinement technique is adopted, so that high accuracy is achieved with a relative low computational cost. Phase-change phenomena (evaporation of the heavy gasoil droplet), as well as catalytic cracking surface reactions are taken into account. Physical properties of heavy and light molecular weight hydrocarbons are modeled by representative single component species, while a 2-lump scheme is proposed for the catalytic cracking reactions. The numerical model is firstly validated for the case of a single liquid droplet evaporation inside a hot gaseous medium and impingement onto a flat wall for droplet heating and film boiling conditions. Afterwards, it is utilized for the prediction of single droplet-catalyst collisions inside the FCC injection zone. The numerical results indicate that droplets of similar size to the catalytic particles tend to be levitated more easily by hot catalysts, thus resulting in higher cracking reaction rates/cracking product yield, and limited possibility for liquid pore blocking. For larger sized droplets, the corresponding results indicate that the production of cracking products is not favored, while solid-liquid contact increases. Hotter catalysts promote catalytic cracking reactions and droplet levitation over the catalytic particle, owed to the formation of a thin vapour layer between the liquid and the solid particle.

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“…As a consequence, lumping of components according to the boiling range and specific properties is generally accepted. [11 -14] Several kinetic models for the FCC process have been proposed by now, with different number of lumps taken into account: three lumps, [15] four lumps, [16] five lumps [11,12,17 -19] or even ten lumps. [20] All these kinetic models consider the gaseous products as forming a pseudo component.…”

Section: First Principle Modelmentioning

confidence: 99%

FCCU simulation based on first principle and artificial neural network models

Miheţ

Cristea

Agachi

2009

Asia-Pacific J Chem Eng

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A first principle model has been developed for the reactor-regenerator system based on construction and operating data from an industrial fluid catalytic cracking unit (FCCU). The first principle model takes into account the main FCCU subsystems: reactor riser, regenerator, stripper, catalyst circulation lines, air blower, wet gas compressor and main fractionator. A five-lump kinetic scheme has been considered for the reactions taking place in the reactor riser. Subsequently, an artificial neural network (ANN) model has been built for the complex FCCU system. The dynamic simulator, based on the previously developed first principle model, served as the source of reliable data for ANN design, training and testing. The ANN developed model was successfully trained and tested. Comparison between first principle and neural network based model leads to a very good match between the two models. Results show the substantial reduction of the computation time featured by the ANN model compared to the first principle model, demonstrating its potential use for real-time implementation in model-based control algorithms.  2009 Curtin

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Fluid Catalytic Cracking Catalyst for Reformulated Gasolines. Kinetic Modeling

Cited by 62 publications

References 7 publications

Experimental methods in chemical engineering: Reactors—fluidized beds

Experimental methods in chemical engineering: Reactors—fluidized beds

Numerical investigation of heavy fuel droplet-particle collisions in the injection zone of a Fluid Catalytic Cracking reactor, Part I: Numerical model and 2D simulations

FCCU simulation based on first principle and artificial neural network models

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